Role summary
we are seeking a highly skilled and experienced machine learning engineer to join our team. This role is ideal for someone who has a strong background in designing and implementing automated machine learning pipelines, building scalable data workflows using pyspark and apache spark within databricks, and collaborating with data scientists and actuaries to package models and deliver reproducible solutions.
key responsibilities:
* develop and implement efficient ml pipelines for training, testing, deployment, and monitoring of models used in insurance applications such as claims prediction, fraud detection, and policy pricing.
* collaborate with cross-functional teams to ensure ml models are production-ready, scalable, and resilient.
* design and implement scalable data workflows using pyspark and apache spark within databricks.
* implement continuous integration and delivery (ci/cd) pipelines for ml using tools such as mlflow, azure devops, or github actions.
* ensure compliance with data privacy, regulatory standards, and model governance practices required in the insurance sector.
required skills:
* strong background in machine learning engineering, including experience with popular libraries and frameworks.
* proficiency in programming languages such as python and r.
* experience with data science tools such as pyspark, apache spark, and databricks.
* knowledge of ci/cd pipelines and automation tools such as mlflow, azure devops, or github actions.
* strong understanding of data privacy and regulatory standards.
benefits:
* opportunity to work with a talented team of data scientists, engineers, and actuaries.
* professional development opportunities to enhance skills and knowledge.
* a dynamic and supportive work environment that fosters innovation and creativity.